PROJECT SUMMARY Parent grant R01DA044608 uses resting-state and task-based functional MRI (fMRI) to map the neural underpinnings of prospection, or the ability to vividly pre-experience future events to forecast consequences of daily decisions. Yet while fMRI has become the leading technology for exploring brain-behavior relationships (as evidenced by the ABCD Project), the confounding influence of head motion on fMRI BOLD signal remains unresolved. Numerous denoising approaches have been proposed to mitigate the impact of head motion on BOLD signal, but the ideal solution is to minimize or prevent head motion during data acquisition. Toward this goal, we have piloted the use of CaseForge custom-fitting head stabilizers to reduce head motion during fMRI scanning. Based upon our encouraging pilot data, the proposed supplement seeks funding to establish an on- site CaseForge CNC machine to generate head stabilizers for remaining R01DA044608 participants, including adolescents (ages 12-16) at risk for initiating drug use and adults (ages 25-50) with or without cocaine use disorder. We will also partner with the Child Mind Institute (CMI, New York) to extend these findings to their Healthy Brain Network (HBN) study, which is acquiring a broad developmental sample of children ages 5-21 with varying psychiatric diagnoses. Aim 1 will evaluate head stabilizer tolerability by comparing retention rates for participants using the stabilizer against retention rates of participants scanned over the previous year. We hypothesize that retention rates will not significantly differ between participant cohorts. Aim 2 will quantify the utility of head stabilizers for reducing head motion. Each site will conduct case-control cross-sectional designs matching participants scanned with the stabilizer to demographically and clinically matched participants from existing data repositories. We hypothesis that head motion (assessed by framewise displacement, FD) will be significantly reduced for participants scanned with the stabilizers. Aim 3 (UAMS only) will test if quality of head stabilizer fit to the participant's head predicts its ability to reduce head motion. Our anecdotal experience in 9- 10 year olds is that individual variance in head shape leads to variance in stabilizer fit, which may influence head motion reduction. We will empirically test this by introducing a volitional movement fMRI task in which participants are prompted to move their heads; we predict that median within-task FD will predict median rs- fMRI FD, validating the influence of stabilizer fit on motion reduction. Finally, Aim 4 (CMI only) will employ a classifier that uses one minute of rs-fMRI data to predict the likelihood of a participant generating quality-pass data for entire rs-fMRI session. Participants will undergo a separate one-minute rs-fMRI scan without stabilizer; linear regression will test with estimated data quality without stabilizer significantly differs from actual data quality with stabilizer, demonstrating its benefit. Collectively, these aims will empirically evaluate the feasibility and utility of CaseForge head stabilizers for reducing head motion during rs-fMRI scans.